----------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\jar68\OneDrive\Ongoing Work\Party Cues and Suspicion Paper\Final Datavserse\Table3\table3_log.lo
> g
  log type:  text
 opened on:  25 Jun 2021, 16:56:48

. 
. ***********************Merged Analyses
. encode experiment, gen(exp)

. label var exp "Experiment"

. label var support01 "Policy Support"

. 
. **Analyses
. eststo clear

. eststo: regress support01 i.treat i.exp

      Source |       SS           df       MS      Number of obs   =     5,820
-------------+----------------------------------   F(5, 5814)      =     14.26
       Model |  5.70036635         5  1.14007327   Prob > F        =    0.0000
    Residual |  464.934275     5,814  .079968056   R-squared       =    0.0121
-------------+----------------------------------   Adj R-squared   =    0.0113
       Total |  470.634641     5,819  .080878955   Root MSE        =    .28279

------------------------------------------------------------------------------------
         support01 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
             treat |
        Party Cue  |   .0817108    .009995     8.18   0.000     .0621169    .1013046
Cue w/Insinuation  |   .0360011    .009201     3.91   0.000     .0179638    .0540384
                   |
               exp |
     Experiment 2  |  -.0005439   .0113815    -0.05   0.962    -.0228559    .0217681
     Experiment 3  |    .014119   .0107352     1.32   0.188     -.006926     .035164
     Experiment 4  |   .0157378   .0135341     1.16   0.245     -.010794    .0422696
                   |
             _cons |   .4627043   .0105006    44.06   0.000     .4421191    .4832894
------------------------------------------------------------------------------------
(est1 stored)

.         *test
.         test _b[2.treat] = _b[3.treat]

 ( 1)  2.treat - 3.treat = 0

       F(  1,  5814) =   24.84
            Prob > F =    0.0000

.         *lincom
.         lincom _b[2.treat] - _b[3.treat]

 ( 1)  2.treat - 3.treat = 0

------------------------------------------------------------------------------
   support01 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0457097    .009171     4.98   0.000     .0277312    .0636882
------------------------------------------------------------------------------

. 
. eststo: regress support01 i.treat i.exp i.stereo

      Source |       SS           df       MS      Number of obs   =     4,807
-------------+----------------------------------   F(5, 4801)      =     24.55
       Model |  9.87853721         5  1.97570744   Prob > F        =    0.0000
    Residual |  386.423801     4,801   .08048819   R-squared       =    0.0249
-------------+----------------------------------   Adj R-squared   =    0.0239
       Total |  396.302338     4,806  .082459912   Root MSE        =     .2837

------------------------------------------------------------------------------------
         support01 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
             treat |
        Party Cue  |   .0922233   .0112583     8.19   0.000     .0701519    .1142947
Cue w/Insinuation  |   .0452122   .0102249     4.42   0.000     .0251667    .0652576
                   |
               exp |
     Experiment 3  |   .0142051   .0094161     1.51   0.131    -.0042547    .0326649
     Experiment 4  |    .017447   .0124832     1.40   0.162    -.0070258    .0419199
                   |
            stereo |
    Stereotypical  |   .0597056   .0081866     7.29   0.000     .0436561    .0757552
             _cons |   .4257469    .010394    40.96   0.000       .40537    .4461238
------------------------------------------------------------------------------------
(est2 stored)

.         *test
.         test _b[2.treat] = _b[3.treat]

 ( 1)  2.treat - 3.treat = 0

       F(  1,  4801) =   21.46
            Prob > F =    0.0000

.         *lincom
.         lincom _b[2.treat] - _b[3.treat]

 ( 1)  2.treat - 3.treat = 0

------------------------------------------------------------------------------
   support01 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0470111   .0101485     4.63   0.000     .0271155    .0669068
------------------------------------------------------------------------------

. 
. eststo: regress support01 i.treat##i.stereo i.exp

      Source |       SS           df       MS      Number of obs   =     4,807
-------------+----------------------------------   F(7, 4799)      =     17.85
       Model |   10.057745         7  1.43682072   Prob > F        =    0.0000
    Residual |  386.244593     4,799  .080484391   R-squared       =    0.0254
-------------+----------------------------------   Adj R-squared   =    0.0240
       Total |  396.302338     4,806  .082459912   Root MSE        =     .2837

--------------------------------------------------------------------------------------------------
                       support01 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------------+----------------------------------------------------------------
                           treat |
                      Party Cue  |   .0960329   .0158277     6.07   0.000     .0650033    .1270624
              Cue w/Insinuation  |    .035538   .0142067     2.50   0.012     .0076862    .0633897
                                 |
                          stereo |
                  Stereotypical  |   .0525003   .0160357     3.27   0.001     .0210629    .0839377
                                 |
                    treat#stereo |
        Party Cue#Stereotypical  |  -.0078819   .0225132    -0.35   0.726    -.0520181    .0362544
Cue w/Insinuation#Stereotypical  |   .0197937   .0199869     0.99   0.322    -.0193898    .0589772
                                 |
                             exp |
                   Experiment 3  |   .0141335   .0094163     1.50   0.133    -.0043267    .0325937
                   Experiment 4  |   .0177843   .0124851     1.42   0.154    -.0066922    .0422609
                                 |
                           _cons |   .4292977   .0124295    34.54   0.000     .4049301    .4536653
--------------------------------------------------------------------------------------------------
(est3 stored)

.         margins, dydx(treat) by(stereo) 

Average marginal effects                        Number of obs     =      4,807
Model VCE    : OLS

Expression   : Linear prediction, predict()
dy/dx w.r.t. : 2.treat 3.treat
over         : stereo

----------------------------------------------------------------------------------------
                       |            Delta-method
                       |      dy/dx   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
1.treat                |  (base outcome)
-----------------------+----------------------------------------------------------------
2.treat                |
                stereo |
Counter-Stereotypical  |   .0960329   .0158277     6.07   0.000     .0650033    .1270624
        Stereotypical  |    .088151   .0160136     5.50   0.000     .0567571    .1195449
-----------------------+----------------------------------------------------------------
3.treat                |
                stereo |
Counter-Stereotypical  |    .035538   .0142067     2.50   0.012     .0076862    .0633897
        Stereotypical  |   .0553317   .0143889     3.85   0.000     .0271228    .0835405
----------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

.         margins, dydx(treat) by(stereo) post coeflegend

Average marginal effects                        Number of obs     =      4,807
Model VCE    : OLS

Expression   : Linear prediction, predict()
dy/dx w.r.t. : 2.treat 3.treat
over         : stereo

----------------------------------------------------------------------------------------
                       |      dy/dx  Legend
-----------------------+----------------------------------------------------------------
1.treat                |  (base outcome)
-----------------------+----------------------------------------------------------------
2.treat                |
                stereo |
Counter-Stereotypical  |   .0960329  _b[2.treat:1bn.stereo]
        Stereotypical  |    .088151  _b[2.treat:2.stereo]
-----------------------+----------------------------------------------------------------
3.treat                |
                stereo |
Counter-Stereotypical  |    .035538  _b[3.treat:1bn.stereo]
        Stereotypical  |   .0553317  _b[3.treat:2.stereo]
----------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

.         *Stereotypical
.         test _b[2.treat:2.stereo] =  _b[3.treat:2.stereo]

 ( 1)  [2.treat]2.stereo - [3.treat]2.stereo = 0

       F(  1,  4799) =    5.23
            Prob > F =    0.0223

.         lincom _b[2.treat:2.stereo] - _b[3.treat:2.stereo]

 ( 1)  [2.treat]2.stereo - [3.treat]2.stereo = 0

------------------------------------------------------------------------------
             |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0328193   .0143516     2.29   0.022     .0046837     .060955
------------------------------------------------------------------------------

.         
.         *Counter-stereotypical
.          test _b[2.treat:1bn.stereo] =   _b[3.treat:1bn.stereo]

 ( 1)  [2.treat]1bn.stereo - [3.treat]1bn.stereo = 0

       F(  1,  4799) =   18.66
            Prob > F =    0.0000

.          lincom _b[2.treat:1bn.stereo] -   _b[3.treat:1bn.stereo]

 ( 1)  [2.treat]1bn.stereo - [3.treat]1bn.stereo = 0

------------------------------------------------------------------------------
             |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0604949   .0140059     4.32   0.000     .0330368     .087953
------------------------------------------------------------------------------

. 
. **Full Table (Appendix)**
. esttab using tableob9.rtf, replace onecell label b(2) se star(+ 0.1 * 0.05 ** 0.01) ///
>         title("{\b Table OB9}: Table 3 Results (Experiments 1-4 Merged)") ///
>         nobaselevels
(tabulating estimates stored by eststo; specify "." to tabulate the active results)
(note: file tableob9.rtf not found)
(output written to tableob9.rtf)

. 
. **Truncated Table (In-Text)**
. 
. esttab using table3.rtf, replace onecell label b(2) se star(+ 0.1 * 0.05 ** 0.01) ///
>         title("{\b Table 3}: Experiments 1-4 Merged") ///
>         nobaselevels keep(2.treat 3.treat 2.stereo 2.treat#2.stereo 3.treat#2.stereo) ///
>         addnote("See Table OB9 for experiment fixed effects and Table OB10 for analyses that further control for pre
> -treatment demographics.")
(tabulating estimates stored by eststo; specify "." to tabulate the active results)
(note: file table3.rtf not found)
(output written to table3.rtf)

.         
.         
. /*******************************
> Controls
> *******************************/
. 
. label var pid_ext "PID Extremity"

. label def pi 2 "Leaning Partisan" 3 "Not Strong Partisan" 4 "Strong Partisan"

. label values pid_ext pi 

. 
. label var ideology "Symbolic Ideology"

. 
. label var age "Age"

. 
. label var gender "Gender"

. label def gend 1 "Female" 0 "Male"

. label values gender gend

. 
. label var race_eth "Race/Ethnicity"

. label def rac 1 "White" 2 "Black" 3 "Hispanic" 4 "Asian" 5 "Other Race"

. label values race_eth rac

. 
. label var educ "Education" 

. label def ed 1 "HS or Less" 2 "Some College" 3 "BA Degree" 4 "Post-BA Degree"

. label values educ ed

. 
. label var income "Income"

. 
. 
. **Analyses
. eststo clear

. eststo: regress support01 i.treat i.exp ideology i.pid_ext age i.gender i.race_eth i.educ 

      Source |       SS           df       MS      Number of obs   =     5,330
-------------+----------------------------------   F(17, 5312)     =     10.32
       Model |  13.7158926        17  .806817214   Prob > F        =    0.0000
    Residual |  415.490019     5,312  .078217247   R-squared       =    0.0320
-------------+----------------------------------   Adj R-squared   =    0.0289
       Total |  429.205911     5,329  .080541548   Root MSE        =    .27967

--------------------------------------------------------------------------------------
           support01 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
               treat |
          Party Cue  |   .0887929     .01024     8.67   0.000     .0687183    .1088675
  Cue w/Insinuation  |   .0374405   .0094847     3.95   0.000     .0188466    .0560344
                     |
                 exp |
       Experiment 2  |  -.0016157   .0114006    -0.14   0.887    -.0239655    .0207342
       Experiment 3  |   .0239202   .0115137     2.08   0.038     .0013486    .0464918
       Experiment 4  |   .0199932   .0135301     1.48   0.140    -.0065313    .0465177
                     |
            ideology |  -.0017058   .0021324    -0.80   0.424    -.0058861    .0024746
                     |
             pid_ext |
Not Strong Partisan  |   .0069725   .0104332     0.67   0.504    -.0134808    .0274258
    Strong Partisan  |    .054415   .0101313     5.37   0.000     .0345535    .0742766
                     |
                 age |  -.0013808   .0002875    -4.80   0.000    -.0019445   -.0008171
                     |
              gender |
             Female  |  -.0131428   .0077854    -1.69   0.091    -.0284053    .0021197
                     |
            race_eth |
              Black  |   .0071104   .0135315     0.53   0.599     -.019417    .0336378
           Hispanic  |   .0365178   .0126164     2.89   0.004     .0117846     .061251
              Asian  |   .0088734   .0179417     0.49   0.621    -.0262997    .0440465
         Other Race  |   -.001045   .0333839    -0.03   0.975    -.0664911    .0644012
                     |
                educ |
       Some College  |  -.0008374   .0122199    -0.07   0.945    -.0247934    .0231186
          BA Degree  |    .004236   .0125123     0.34   0.735    -.0202932    .0287652
     Post-BA Degree  |   .0236704   .0147264     1.61   0.108    -.0051994    .0525403
                     |
               _cons |   .4911521   .0214888    22.86   0.000     .4490253    .5332789
--------------------------------------------------------------------------------------
(est1 stored)

.         *test
.         test _b[2.treat] = _b[3.treat]

 ( 1)  2.treat - 3.treat = 0

       F(  1,  5312) =   29.25
            Prob > F =    0.0000

.         *lincom
.         lincom _b[2.treat] - _b[3.treat]

 ( 1)  2.treat - 3.treat = 0

------------------------------------------------------------------------------
   support01 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0513524   .0094953     5.41   0.000     .0327378     .069967
------------------------------------------------------------------------------

. 
. eststo: regress support01 i.treat i.exp i.stereo ideology i.pid_ext age i.gender i.race_eth i.educ 

      Source |       SS           df       MS      Number of obs   =     4,338
-------------+----------------------------------   F(17, 4320)     =     13.68
       Model |  18.2020174        17  1.07070691   Prob > F        =    0.0000
    Residual |  338.077392     4,320  .078258656   R-squared       =    0.0511
-------------+----------------------------------   Adj R-squared   =    0.0474
       Total |   356.27941     4,337  .082148815   Root MSE        =    .27975

--------------------------------------------------------------------------------------
           support01 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
               treat |
          Party Cue  |   .1009195   .0115783     8.72   0.000     .0782201    .1236189
  Cue w/Insinuation  |    .047583   .0105797     4.50   0.000     .0268414    .0683245
                     |
                 exp |
       Experiment 3  |   .0309163   .0105157     2.94   0.003        .0103    .0515325
       Experiment 4  |   .0219527   .0124697     1.76   0.078    -.0024943    .0463996
                     |
              stereo |
      Stereotypical  |   .0637149   .0085215     7.48   0.000     .0470083    .0804215
            ideology |  -.0066509   .0023574    -2.82   0.005    -.0112726   -.0020292
                     |
             pid_ext |
Not Strong Partisan  |  -.0036966   .0115968    -0.32   0.750    -.0264323    .0190391
    Strong Partisan  |    .051218   .0111151     4.61   0.000     .0294267    .0730093
                     |
                 age |  -.0012722   .0003113    -4.09   0.000    -.0018825    -.000662
                     |
              gender |
             Female  |  -.0221919   .0086202    -2.57   0.010     -.039092   -.0052919
                     |
            race_eth |
              Black  |  -.0009997   .0148432    -0.07   0.946    -.0301001    .0281006
           Hispanic  |    .032194   .0139595     2.31   0.021     .0048263    .0595618
              Asian  |   .0110651   .0206791     0.54   0.593    -.0294764    .0516067
         Other Race  |  -.0243488   .0365661    -0.67   0.506    -.0960373    .0473396
                     |
                educ |
       Some College  |   .0051379   .0134244     0.38   0.702    -.0211808    .0314566
          BA Degree  |   .0143417    .013842     1.04   0.300    -.0127957    .0414791
     Post-BA Degree  |   .0392104   .0162797     2.41   0.016      .007294    .0711269
                     |
               _cons |   .4656807   .0226184    20.59   0.000      .421337    .5100244
--------------------------------------------------------------------------------------
(est2 stored)

.         *test
.         test _b[2.treat] = _b[3.treat]

 ( 1)  2.treat - 3.treat = 0

       F(  1,  4320) =   25.49
            Prob > F =    0.0000

.         *lincom
.         lincom _b[2.treat] - _b[3.treat]

 ( 1)  2.treat - 3.treat = 0

------------------------------------------------------------------------------
   support01 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0533365   .0105639     5.05   0.000     .0326259    .0740472
------------------------------------------------------------------------------

. 
. eststo: regress support01 i.treat##i.stereo i.exp ideology i.pid_ext age i.gender i.race_eth i.educ 

      Source |       SS           df       MS      Number of obs   =     4,338
-------------+----------------------------------   F(19, 4318)     =     12.34
       Model |  18.3422652        19  .965382377   Prob > F        =    0.0000
    Residual |  337.937145     4,318  .078262424   R-squared       =    0.0515
-------------+----------------------------------   Adj R-squared   =    0.0473
       Total |   356.27941     4,337  .082148815   Root MSE        =    .27975

--------------------------------------------------------------------------------------------------
                       support01 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------------+----------------------------------------------------------------
                           treat |
                      Party Cue  |   .1047199   .0163001     6.42   0.000     .0727633    .1366765
              Cue w/Insinuation  |   .0387104   .0146426     2.64   0.008     .0100034    .0674174
                                 |
                          stereo |
                  Stereotypical  |   .0573983   .0164407     3.49   0.000     .0251661    .0896305
                                 |
                    treat#stereo |
        Party Cue#Stereotypical  |  -.0076685   .0231351    -0.33   0.740    -.0530252    .0376882
Cue w/Insinuation#Stereotypical  |   .0182802   .0206826     0.88   0.377    -.0222684    .0588288
                                 |
                             exp |
                   Experiment 3  |   .0309582   .0105164     2.94   0.003     .0103406    .0515758
                   Experiment 4  |   .0222277   .0124717     1.78   0.075    -.0022233    .0466787
                                 |
                        ideology |    -.00666   .0023578    -2.82   0.005    -.0112825   -.0020375
                                 |
                         pid_ext |
            Not Strong Partisan  |  -.0035695   .0116006    -0.31   0.758    -.0263126    .0191736
                Strong Partisan  |   .0511732   .0111163     4.60   0.000     .0293795    .0729668
                                 |
                             age |  -.0012718   .0003113    -4.09   0.000     -.001882   -.0006615
                                 |
                          gender |
                         Female  |  -.0222436   .0086221    -2.58   0.010    -.0391473   -.0053399
                                 |
                        race_eth |
                          Black  |  -.0006035   .0148505    -0.04   0.968    -.0297181    .0285111
                       Hispanic  |    .032045   .0139603     2.30   0.022     .0046756    .0594144
                          Asian  |   .0107915   .0206806     0.52   0.602     -.029753    .0513361
                     Other Race  |  -.0232267   .0365814    -0.63   0.526    -.0949451    .0484917
                                 |
                            educ |
                   Some College  |   .0052895   .0134284     0.39   0.694    -.0210372    .0316161
                      BA Degree  |   .0146217    .013845     1.06   0.291    -.0125217     .041765
                 Post-BA Degree  |   .0396529   .0162863     2.43   0.015     .0077233    .0715824
                                 |
                           _cons |   .4685226   .0235007    19.94   0.000     .4224493     .514596
--------------------------------------------------------------------------------------------------
(est3 stored)

.         margins, dydx(treat) by(stereo) 

Average marginal effects                        Number of obs     =      4,338
Model VCE    : OLS

Expression   : Linear prediction, predict()
dy/dx w.r.t. : 2.treat 3.treat
over         : stereo

----------------------------------------------------------------------------------------
                       |            Delta-method
                       |      dy/dx   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
1.treat                |  (base outcome)
-----------------------+----------------------------------------------------------------
2.treat                |
                stereo |
Counter-Stereotypical  |   .1047199   .0163001     6.42   0.000     .0727633    .1366765
        Stereotypical  |   .0970514   .0164337     5.91   0.000     .0648329    .1292699
-----------------------+----------------------------------------------------------------
3.treat                |
                stereo |
Counter-Stereotypical  |   .0387104   .0146426     2.64   0.008     .0100034    .0674174
        Stereotypical  |   .0569906   .0149484     3.81   0.000     .0276839    .0862972
----------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

.         margins, dydx(treat) by(stereo) post coeflegend

Average marginal effects                        Number of obs     =      4,338
Model VCE    : OLS

Expression   : Linear prediction, predict()
dy/dx w.r.t. : 2.treat 3.treat
over         : stereo

----------------------------------------------------------------------------------------
                       |      dy/dx  Legend
-----------------------+----------------------------------------------------------------
1.treat                |  (base outcome)
-----------------------+----------------------------------------------------------------
2.treat                |
                stereo |
Counter-Stereotypical  |   .1047199  _b[2.treat:1bn.stereo]
        Stereotypical  |   .0970514  _b[2.treat:2.stereo]
-----------------------+----------------------------------------------------------------
3.treat                |
                stereo |
Counter-Stereotypical  |   .0387104  _b[3.treat:1bn.stereo]
        Stereotypical  |   .0569906  _b[3.treat:2.stereo]
----------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

.         *Stereotypical
.         test _b[2.treat:2.stereo] =  _b[3.treat:2.stereo]

 ( 1)  [2.treat]2.stereo - [3.treat]2.stereo = 0

       F(  1,  4318) =    7.24
            Prob > F =    0.0072

.         lincom _b[2.treat:2.stereo] - _b[3.treat:2.stereo]

 ( 1)  [2.treat]2.stereo - [3.treat]2.stereo = 0

------------------------------------------------------------------------------
             |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0400608   .0148869     2.69   0.007      .010875    .0692467
------------------------------------------------------------------------------

.         
.         *Counter-stereotypical
.          test _b[2.treat:1bn.stereo] =   _b[3.treat:1bn.stereo]

 ( 1)  [2.treat]1bn.stereo - [3.treat]1bn.stereo = 0

       F(  1,  4318) =   20.43
            Prob > F =    0.0000

.          lincom _b[2.treat:1bn.stereo] -   _b[3.treat:1bn.stereo]

 ( 1)  [2.treat]1bn.stereo - [3.treat]1bn.stereo = 0

------------------------------------------------------------------------------
             |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0660095   .0146024     4.52   0.000     .0373814    .0946376
------------------------------------------------------------------------------

. 
. **Full Table (Appendix)**
. *Note: Table OB10 has lincom results in it; these were added manually based on the foregoing command results
. esttab using tableob10.rtf, replace onecell label b(2) se star(+ 0.1 * 0.05 ** 0.01) ///
>         title("{\b Table OB10}: Table 3 Results w/Demographics (Experiments 1-4 Merged)") ///
>         nobaselevels
(tabulating estimates stored by eststo; specify "." to tabulate the active results)
(note: file tableob10.rtf not found)
(output written to tableob10.rtf)

. 
.         
.         
. log close
      name:  <unnamed>
       log:  C:\Users\jar68\OneDrive\Ongoing Work\Party Cues and Suspicion Paper\Final Datavserse\Table3\table3_log.lo
> g
  log type:  text
 closed on:  25 Jun 2021, 16:56:50
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